Optimization Foundation

• Tech Stack: Python, PyTorch, NumPy, OOP
• Github URL: Project Link

Contributed to the repository "optimization_foundation" for research at the Yale Interactive Machines Group Lab. Coded the entire metrics.py and metrics_test.py, which includes metrics for testing the robot's navigation and training an ML model to minimize these metrics.

Coded and tested 12 metrics in Python and PyTorch using functions like sigmoid and OOP concepts such as classes and NumPy by making tensors in PyTorch. Also utilized the Python debugger.

Implemented a range of metrics including robot static obstacle collisions, and designed a loss function to minimize these metrics, enhancing robot navigation performance.

This work is part of a research paper conducted by Yale IMG on social robotic navigation.